Skip to main content

Advertisement

SpringerLink
Log in

The spatial employment effect of high-speed railway: quasi-natural experimental evidence from China

  • Original Paper
  • Published:
The Annals of Regional Science Aims and scope Submit manuscript

Abstract

High-speed rail (HSR) access promotes the interregional population flow and integrated market across cities in China. Using panel data of 286 cities in China from 2000 to 2018, we investigated the spatial employment effect of HSR by multi-period Difference-in-Difference (DID) model and staggered DID. We found that: First, HSR significantly enhances the spatial employment agglomeration, rationalization of three industrial-employment structures and the advancement of industrial structure in areas with HSR. Cities that open HSRs later generally get higher marginal benefit from HSR. Second, based on the change of regional accessibility caused by HSR, income and housing price are two channels affect spatial employment distribution; capital and labor are two channels affect the industrial-employment structure. Third, HSR has a greater spatial employment effect in peripheral cities than central cities, and HSR has a greater spatial employment effect in southern cities than northern cities. HSR has significantly promoted employment agglomeration in eastern China; it has a significant impact on the employment structure in Northeast China. Fourth, the effective radiation distance of HSR station is about 30 km. Labor market needs to pay more attention on the influences of new massive public transportation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

The dataset supporting the conclusions of this article is available from the China city statistical yearbook, the statistics bulletin of the national economy and social development, the national railway bureau website and 12,360 railway website. The datasets used and/or analyzed during the current study are available from the corresponding author on request.

Notes

  1. In this paper, passenger trains with speeds of 200 km/h or above are defined as HSR trains.

  2. By province, Eastern China includes: Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan. Central China includes Shanxi, Anhui, Jiangxi, Henan, Hubei and Hunan. Western China includes: Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang. Northeastern China includes: Liaoning, Jilin and Heilongjiang.

  3. It means the second level of administrative divisions in China. 286 cities in prefecture-level and above were sorted out from the Statistical Yearbook of Chinese Cities from 2001 to 2019, due to the lack of data of some cities and the changes of administrative divisions in the past years.

  4. Southern China includes Hainan, Guangdong, Yunnan, Guangxi, Guizhou, Jiangxi, Fujian, Jiangsu, Anhui, Hunan, Hubei, Sichuan, Chongqing, Shanghai and Zhejiang. Northern China includes Heilongjiang, Jilin, Liaoning, Inner Mongolia, Beijing, Tianjin, Hebei, Henan, Shandong, Xinjiang, Tibet, Gansu, Qinghai, Ningxia, Shaanxi, Shanxi.

  5. It is calculated by the data of China Labor Statistics Yearbook from 2001 to 2019. The spatial Gini coefficient of employed population is consistent with the calculation method of income Gini coefficient. Lorentz curve is drawn according to the cumulative proportion of employed population in urban units to the total employed population in different regions. The higher the coefficient is, the higher the spatial concentration of employment is.

  6. Central cities refer to the cities municipalities directly under the central government, provincial capitals and sub-provincial cities.

References

  • Aguayo-Tellez E, Rivera-Mendoza CI (2011) Migration from Mexico to the United States: wage benefits of crossing the border and going to the U.S. interior. Politics Policy 39:119–140

    Article  Google Scholar 

  • Ahlfeldt GM, Feddersen A (2018) From periphery to core: measuring agglomeration effects using high-speed rail. J Econ Geogr 18:355–390

    Article  Google Scholar 

  • Albalate D, Fageda X (2016) High speed rail and tourism: empirical evidence from Spain. Transp Res Part A Policy Pract 85:174–185

    Article  Google Scholar 

  • Banerjee A, Duflo E, Qian N (2020) On the road: access to transportation infrastructure and economic growth in China. J Dev Econ 145:102442

    Article  Google Scholar 

  • Beck T, Levine R, Levkov A (2010) Big bad banks? The winners and losers from bank deregulation in the United States. J Financ 65:1637–1667

    Article  Google Scholar 

  • Bernard AB, Moxnes A, Saito YU (2014) Production networks, geography and firm performance. J Polit Econ 127(2):639–688

    Article  Google Scholar 

  • Braunerhjelm P, Borgman B (2006) Agglomeration, diversity and regional growth: the effect of poly-industrial versus mono-industrial agglomerations. Electronic working paper series No.71

  • Chen Z, Haynes KE (2017) Impact of high-speed rail on regional economic disparity in China. J Transp Geogr 65:80–91

    Article  Google Scholar 

  • Chenery H, Robinson S, Syrquin M (1986) Industrialization and growth: a comparative study. Oxford University Press, New York

    Google Scholar 

  • Cheng Y-S, Loo BPY, Vickerman R (2015) High-speed rail networks, economic integration and regional specialisation in China and Europe. Travel Behav Soc 2:1–14

    Article  Google Scholar 

  • Degen K, Fischer AM (2017) Immigration and swiss house prices. Swiss Soc Econ Stat 153:15–36

    Article  Google Scholar 

  • Ding S, Ding Y, Wu D (2018) Research on the transformation of employment contradiction from quantity to quality in China. Economist 12:57–63

    Google Scholar 

  • Dohmen TJ (2005) Housing, mobility and unemployment. Reg Sci Urban Econ 35:305–325

    Article  Google Scholar 

  • Donaldson D (2018) Railroads of the Raj: estimating the impact of transportation infrastructure. Am Econ Rev 108:899–934

    Article  Google Scholar 

  • Dong X (2018) High-speed railway and urban sectoral employment in China. Transp Res Part A Policy Pract 116:603–621

    Article  Google Scholar 

  • Dong Y-M, Zhu Y-M (2016) Can high-speed rail construction reshape the layout of China’s economic space—based on the perspective of regional heterogeneity of employment, wage and economic growth. China Ind Econ 10:92–108

    Google Scholar 

  • Duffy-Deno KT, Dalenberg DR (1993) The municipal wage and employment effects of public infrastructure. Urban Stud 30:1577–1589

    Article  Google Scholar 

  • Dumais G, Ellison G, Glaeser, EL (1997) Geographic concentration as a dynamic process. NBER working paper series No.6270

  • Duranton G (2010) Labor specialization, transport costs, and city size. J Reg Sci 38:553–573

    Article  Google Scholar 

  • Duranton G, Turner MA (2012) Urban growth and transportation. Rev Econ Stud 79:1407–1440

    Article  Google Scholar 

  • Faber B (2014) Trade integration, market size, and industrialization: evidence from China’s national trunk highway system. Rev Econ Stud 81:1046–1070

    Article  Google Scholar 

  • Fan S, Zhang X, Robinson S (2003) Structural change and economic growth in China. Rev Dev Econ 7:360–377

    Article  Google Scholar 

  • Forslid R, Ottaviano GIP (2003) An analytically solvable core-periphery model. J Econ Geogr 3:229–240

    Article  Google Scholar 

  • Fujita M, Mori T (1997) Structural stability and evolution of urban systems. Reg Sci Urban Econ 27:399–442

    Article  Google Scholar 

  • Gardner J (2021) A primer on staggered DD. Working paper

  • He X (2019) Analysis and prospect of national labor market and rural development policy. Seeker 01:11–17

    Google Scholar 

  • Heuermann DF, Schmieder JF (2019) The effect of infrastructure on worker mobility evidence from high-speed rail expansion in Germany. J Econ Geogr 19:335–372

    Article  Google Scholar 

  • Imbens GW, Rubin DB (2015) Causal inference for statistics, social, and biomedical sciences. Cambridge University Press, NewYork

    Book  Google Scholar 

  • Jackman R, Savouri S (1992) Regional migration in Britain: an analysis of gross flows using NHS central register data. Econ J 102:1433–1450

    Article  Google Scholar 

  • Johansson B, Klaesson J, Olsson M (2005) Time distances and labor market integration. Pap Reg Sci 81:305–327

    Article  Google Scholar 

  • Kim KS (2000) High-speed rail Developments and Spatial Restructuring: a case study of the capital region in South Korea. Cities 17:251–262

    Article  Google Scholar 

  • Kim H, Sultana S, Weber J (2018) A geographic assessment of the economic development impact of Korean high-speed rail stations. Transp Policy 66:127–137

    Article  Google Scholar 

  • Krugman P (1991) Increasing returns and economic geography. J Polit Econ 99:483–499

    Article  Google Scholar 

  • Leunig T (2006) Time is money: a re-assessment of the passenger social savings from Victorian British railways. J Econ Hist 66:635–673

    Article  Google Scholar 

  • Lin Y (2017) Travel costs and urban specialization patterns: evidence from China’s high speed railway system. J Urban Econ 98:98–123

    Article  Google Scholar 

  • Lin Y, Qin Y, Sulaeman J, Yan J, Zhang J (2020) Expanding footprints:the impact of passenger transportation on corporate locations. Social Science Electronic Publishing. Working paper. No. 15–19

  • Lucas RE (1988) On the mechanics of economic development. J Monet Econ 22:3–42

    Article  Google Scholar 

  • Mackinnon DP, Krull JL, Lockwood CM (2000) Equivalence of the mediation, confounding and suppression effect. Prev Sci 1:173–181

    Article  Google Scholar 

  • Martin P, Rogers CA (1995) Industrial location and public infrastructure. J Int Econ 39:335–351

    Article  Google Scholar 

  • Meen G, Nygaard A (2010) Housing and regional economic disparities. Swiss National Bank Working Papers No. 5

  • Morris JM, Dumble PL, Wigan MR (1979) Accessibility indicators for transport planning. Trangsportation Research Part a: General 13:91–109

    Article  Google Scholar 

  • Munnell AH (1990) Why has productivity growth declined? Productivity and public investment. Engl Econ Rev 30:3–22

    Google Scholar 

  • Ottaviano G, Tabuchi T, Thisse J-F (2002) Agglomeration and trade revisited. Int Econ Rev 43:409–435

    Article  Google Scholar 

  • Peter MJP (2003) The economic impact of the high-speed train on urban regions. Eur Reg Sci Assoc. ERSA conference papers ersa03p397

  • Picard PM, Toulemonde E (2006) Firms agglomeration and unions. Eur Econ Rev 50:669–694

    Article  Google Scholar 

  • Pissarides CA, McMaster I (1990) Regional migration, wages and unemployment empirical evidence and implications for policy. Oxf Econ Pap 42:812–831

    Article  Google Scholar 

  • Qin Y (2017) No county left behind? The distributional impact of high-speed rail upgrades in China. J Econ Geogr 17:489–520

    Google Scholar 

  • Rabe B, Taylor MP (2012) Differences in opportunities? Wage, employment and house-price effects on migration. Oxf Bull Econ Stat 74:831–855

    Article  Google Scholar 

  • Redding SJ, Turner MA (2015) Transportation costs and the spatial organization of economic activity. Handb Reg Urban Econ 5:1339–1398

    Article  Google Scholar 

  • Rosenthal SS, Strange WC (2004) Evidence on the nature and sources of agglomeration economies. Handb Reg Urban Econ 4:2119–2171

    Article  Google Scholar 

  • Shao S, Tian Z, Yang L (2017) High speed rail and urban service industry agglomeration: evidence from China’s Yangtze river delta region. J Transp Geogr 64:174–183

    Article  Google Scholar 

  • Shaw S, Fang Z, Lu S, Tao R (2014) Impacts of high speed rail on railroad network accessibility in China. J Transp Geogr 40:112–122

    Article  Google Scholar 

  • Shi J, Zhou N (2013) How cities influenced by high speed rail development: a case study in China. J Transp Technol 3:7–16

    Google Scholar 

  • Vickerman R (2018) Can high-speed rail have a transformative effect on the economy? Transp Policy 62:31–37

    Article  Google Scholar 

  • Vickerman R (2007) Recent evolution of research into the wider economic benefits of transport infrastructure investments. Joint transport research centre discussion papers

  • Wen Z, Ye B (2014) Analyses of mediating effects: the development of methods and models. Adv Psychol Sci 22:731

    Article  Google Scholar 

  • Yang X, Zhang D (2001) Endogenous structure of division of labor, endogenous policy regime, and a dual structure in economic development. Ann Econ Financ 1:203–221

    Google Scholar 

  • Yin M, Bertolini L, Duan J (2015) The effects of the high-speed railway on urban development: international experience and potential implications for China. Prog Plan 98:1–52

    Article  Google Scholar 

  • Yu F, Lin F, Tang Y, Zhong C (2019) High-speed railway to success? The effects of high-speed rail connection on regional economic development in China. J Reg Sci 59:723–742

    Article  Google Scholar 

Download references

Funding

This work was supported by grants from Chinese National Funding of Social Sciences [Grant No. 18ZDA086]; Chinese National Funding of Social Sciences [Grant No. 20AZD071]. The funding body has no role in the design of the study, data collection, analysis, interpretation of the data and write up of the manuscript.

Author information

Authors and Affiliations

  1. School of Economics and Management, Beijing Jiaotong University, No.3 Shangyuan Village, Haidian District, Beijing, 100044, China

    Yahong Liu, Daisheng Tang, Tao Bu & Xinyuan Wang

  2. Beijing Laboratory of National Economic Security Early-warning Engineering, Beijing Jiaotong University, No.3 Shangyuan Village, Haidian District, Beijing, 100044, China

    Daisheng Tang

Authors
  1. Yahong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daisheng Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tao Bu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xinyuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YL: Conceptualization, Software, Formal analysis, Writing-original draft and Writing-Reviewing. DT: Funding acquisition. TB: Data curation. XW: Editing.

Corresponding author

Correspondence to Daisheng Tang.

Ethics declarations

Conflict of interest

All the authors listed have approved the manuscript that is enclosed. The authors declare that there are no financial or other relationships that might lead to a conflict of interest of the present article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Acknowledgements: Thank for the China city statistical yearbook, the statistics bulletin of the national economy and social development, the national railway bureau website and 12360 railway website data supporting.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 2721 KB)

Appendix

Appendix

This paper constructs the time point of counterfactual policy to conduct placebo test. If the employment effect of HSR is not significant under the time point of virtual policy, it proves the robustness of the conclusion. According to the actual opening time of HSR in each city, the net employment effect of HSR opening was estimated by advancing the policy time points of HSR opening in each region by one to five years respectively. Table

Table 9 Placebo test of the spatial employment effect of HSR in 286 cities in China from 2000 to 2018
Full size table

9 shows that the regression coefficients were not significant. These all proved the robustness of the results.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Y., Tang, D., Bu, T. et al. The spatial employment effect of high-speed railway: quasi-natural experimental evidence from China. Ann Reg Sci 69, 333–359 (2022). https://doi.org/10.1007/s00168-022-01135-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00168-022-01135-9

JEL Classification

Search

Navigation